Enhanced minimum-cost conflict risk mitigation-based FMEA for risk assessment in a probabilistic linguistic context

Abstract

Failure mode and effect analysis (FMEA) is a system reliability analysis technique used in various industries to identify, mitigate, and eliminate failure risks. However, the classical FMEA paradigm has limitations in managing complex and uncertain environments. Complex decisions usually involve the participation of multiple decision-makers, and differences between individual assessments are almost inevitable. Reducing differences requires some decision-makers to adjust their assessments, which implies cost and resource consumption. This study proposes a novel FMEA model for risk assessment, which combines minimum-cost conflict risk mitigation (MCCRM) and probabilistic linguistic information. First, probabilistic linguistic term sets are used to describe the risk assessments in response to uncertainty and fuzziness. The MCCRM process is then integrated into FMEA to reduce the differences among individual risk assessments at the minimum adjustment cost. The process incorporates a new consensus constraint, called the explicit adjustment constraint, into classical MCCRM to ensure the movement of individuals to the group assessment. On this basis, two types of enhanced MCCRM models are proposed, which concretize adjustment amounts and overcome the limitation of over-adjustment caused by classical MCCRM. Finally, the feasibility of the proposed model is illustrated by taking the risk assessment of global production base selection as a case.